Anno accademico 2016/2017 - 2° anno
Docente: Giovanni CELANO
Crediti: 9
Organizzazione didattica: 225 ore d'impegno totale, 171 di studio individuale, 54 di lezione frontale

Prerequisiti richiesti

Passing the course: Programmazione e Controllo della Produzione

It is also required to have good knowledge about the manufacturing systems classification and their performance metrics.

Frequenza lezioni

Class attendance is mandatory.

Programmazione del corso

 *ArgomentiRiferimenti testi
1*The Meaning of Quality and its Dimensions. Quality Improvement (QI). Quality Engineering Terminology. Text 1, Ch. 1 
2*ISO 9000 quality standards and their evolution, Certification and accreditation, Audits, ISO 9001-2015. Structure, Context of the Organization, Risk-based thinking. Text 2 Ch.1, Ch. 2, Ch.4, Ch.9 
3 Quality and Productivity, Supply Chain Quality Management, Quality CostsText 1, Ch. 1 
4*The Six Sigma Philosophy: Meaning of Six Sigma, The Six Sigma Roles, The DMAIC Process Steps. DFSS. Lean and Six SigmaText 1, Ch. 1, Text 3, Ch. 8 
5 Case studiesText 3, Ch. 9 
6*Describing variation: Histogram, Box Plot and Dot Plot. Discrete distributions. Continuous distributions: Text 1, Ch. 3 
7*Probability Plots. The Normal Approximation to the Binomial.Text 1, Ch. 3 
8*Selected exercises: 3.1-3.26, 3.29-3.50Text 1, Ch. 3 
9*Statistics and Sampling Distributions. Sampling from a Normal, Binomial and Poisson Distribution. Point Estimation of Process Parameters. Statistical Inference for a Single Sample. Inference on the Mean of a Normal Distribution, (z-test and t-test)Text 1, Ch. 4 
10*Confidence Intervals. The p-value approach. Inference on the Variance of a Normal Distribution, (chi-squared-test). Inference on a Population Proportion and Confidence Interval. The OC curve for the z-test: Choice of the Sample Size. Text 1, Ch. 4 
11*Statistical Inference for Two Samples. Inference for a Difference in Means, (z-test and t-test), Confidence Intervals. Inference on the Variances of a Normal Distribution, (F-test), Confidence Interval. Inference on Two Pop. Proportions and Conf. Int.Text 1, Ch. 4 
12*Inference on More Than Two Populations: the Analysis of Variance.Text 1, Ch. 4 
13*Selected exercises: 4.1-4.21, 4.29, 4.31, 4.33-4.35, 4.37-4.40, 4.43-4.51.Text 1, Ch. 4 
14*Chance and Assignable Causes. Statistical Basis of the Control Chart. Choice of Control Limits. Sample Size and Sampling Frequency. Rational Subgroups. Analysis of Patterns. Adding Sensitizing Rules to Control Charts. Text 1, Ch. 5 
15*Phase I and II Implementation of Control Charts. The Rest of Magnificent Seven: Pareto Chart, Cause and Effect Diagram. Text 1, Ch. 5 
16*Control Charts for xbar and R. Control Charts for Xbar and s: Construction and Operation of Xbar and s Charts; the Xbar and s Control Charts with Variable Sample Size. The Shewhart Control Chart for Individual Measurements. Text 1, Ch. 6 
17*Shewhart Control Charts for Attributes. Control Charts for Fraction Nonconforming (p Charts); Control Charts for Nonconformities (c and u Charts). Procedures with variable sample size Text 1, Ch. 7 
18*Selected exercises: 6.1-6.10,6.15-6.61, 7.1-7.31,7.36-7.60Text 1, Ch. 6-7 
19*Introduction. Process Capability Ratios: Cp, Cpk, Cpm, Cpkm. Process Capability Analysis with Control Charts and Designed Experiments. Process Capability Analysis with Attribute Data. Text 1, Ch. 8, Text 4 
20*Measurement system analysis: resolution, bias, precision. Gauge R&R Analysis. Setting Specification Limits and Estimating the Natural Tolerance Limits. Six Sigma Metrics: ppm, DPMO, yield. Text 1, Taxt 4. Ch. 8, Additional material provided by the course instructor 
21*Selected exercises: 8.1-8.16, 8.23-8.29, 8.30-8.33, 8.36, 8.37Text 1, Ch. 8 
22*The Cumulative Sum Control Chart. Tabular CUSUM for Monitoring the Process Mean. Recommendations for CUSUM Design. The Standardized CUSUM. The Exponentially Weighted Moving Average Control Chart for Monitoring the Process MeanText 1, Ch. 9 
23*The Multivariate Quality-Control Problem. Description of Multivariate Data. The Hotelling T2 Control Chart for Subgrouped Data and Individual ObservationsText 1, Ch. 11 
24*Selected exercises: 11.1-11.9Text 1, Ch. 11 
25*What is Experimental Design? Examples of Designed Experiments in Process and Product Improvement, Guidelines for Designing Experiments. Factorial Experiments. The 2k Factorial Design. Linear Regression Models for Process Characterization and Optimization.Text 1, Ch. 4,13 
* Conoscenze minime irrinunciabili per il superamento dell'esame.

N.B. La conoscenza degli argomenti contrassegnati con l'asterisco è condizione necessaria ma non sufficiente per il superamento dell'esame. Rispondere in maniera sufficiente o anche più che sufficiente alle domande su tali argomenti non assicura, pertanto, il superamento dell'esame.

Verifica dell'apprendimento

Modalità di verifica dell'apprendimento

Grading for this course is determined by a written exam consisting of quantitative exercises and open questions.

Esempi di domande e/o esercizi frequenti

Examples of questions and frequent exercises are provided in the studium area of the course